Joel H. Helquist, Amit Deokar, Jordan J. Cox and Alyssa Walker
The purpose of this paper is to propose virtual process simulation as a technique for identifying and analyzing uncertainty in processes. Uncertainty is composed of both risks and…
Abstract
Purpose
The purpose of this paper is to propose virtual process simulation as a technique for identifying and analyzing uncertainty in processes. Uncertainty is composed of both risks and opportunities.
Design/methodology/approach
Virtual process simulation involves the creation of graphical models representing the process of interest and associated tasks. Graphical models representing the resources (e.g. people, facilities, tools, etc.) are also created. The members of the resources graphical models are assigned to process tasks in all possible combinations. Secondary calculi, representing uncertainty, are imposed upon these models to determine scores. From the scores, changes in process structure or resource allocation can be used to manage uncertainty.
Findings
The example illustrates the benefits of utilizing virtual process simulation in process pre‐planning. Process pre‐planning can be used as part of strategic or operational uncertainty management.
Practical implications
This paper presents an approach to clarify and assess uncertainty in new processes. This modeling technique enables the quantification of measures and metrics to assist in systematic uncertainty analysis. Virtual process simulation affords process designers the ability to more thoroughly examine uncertainty while planning processes.
Originality/value
This research contributes to the study of uncertainty management by promoting a systematic approach that quantifies metrics and measures according to the objectives of a given process.
Details
Keywords
Joel H. Helquist, Jordan J. Cox and Alyssa Walker
The purpose of this paper is to present a virtual process simulation technique for modeling process alternatives.
Abstract
Purpose
The purpose of this paper is to present a virtual process simulation technique for modeling process alternatives.
Design/methodology/approach
The paper proposes modeling method and applies it to an illustrative example.
Findings
The method is effective in modeling the illustrative example and provides a method for studying team composition and dynamics a priori.
Practical implications
The paper presents an approach to model process alternatives in order to select the best deployment option. The modeling process incorporates measures and metrics relating to global geographic and team issues. Incorporation of these issues affords the process designer the ability to predict more accurately the most successful deployment option.
Originality/value
The research contributes to the study of process modeling by examining the potentially neglected or ignored issues relating to geographic and team diversity.